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In this installment of Tips & Tricks we detail one of the many reports available in Forecast Pro TRAC–the Actual vs. Archive report. This important report allows you to track your forecasts’ accuracy by comparing them to what actually occurred. Tracking accuracy provides several benefits such as: information that enables you to improve forecast performance; insight into expected performance; and the ability to spot problems early on.

Error measurement statistics play a critical role in tracking forecast accuracy, monitoring for exceptions, and benchmarking your forecasting process. Interpretation of these statistics can be tricky, particularly when working with low-volume data or when trying to assess accuracy across multiple items (e.g., SKUs, locations, customers, etc.). This installment of Forecasting 101 surveys common error measurement statistics, examines the pros and cons of each and discusses their suitability under a variety of circumstances.

To meet its customers’ needs, Enesco Limited—a worldwide distributor of gifts, home décor and collectables—has the challenging task of creating accurate forecasts for a large number of SKUs. In this case study, you will learn how the UK-based company shortened its lead time for existing products, cut inventory and reduced product shortages by implementing Forecast Pro.

Forecast Pro TRAC provides a wide array of exception reports, including reports which monitor your archived forecasts (i.e., previously created and saved forecasts) and reports which monitor your current forecasts (i.e., the forecasts you are working with but haven’t yet finalized). Exception reports enable you to quickly find cases where key performance metrics have fallen outside of an acceptable range. In this installment of Forecast Pro Tips & Tricks we look at the Forecasts vs. History Exception Report which monitors current forecasts.

Forecast Pro TRAC provides a wide array of exception reports, including reports which monitor your archived forecasts (i.e., previously created and saved forecasts) and reports which monitor your current forecasts (i.e., the forecasts you are working on but haven’t yet finalized). Exception reports enable you to quickly find cases where your forecast error or some other performance metric has fallen outside of an acceptable range. In this article we explain in detail how to create the Waterfall Exception Report to monitor forecast accuracy.

Here’s a question that we get all the time: what forecast accuracy should we target? The answer varies widely across industries and organizations–there is no single “optimal” forecast accuracy (other than 100% accuracy, which is not practical)! The one universal answer is that forecast accuracy can be considered “good” when it is an improvement over the accuracy of the last forecast cycle, and the only way to determine this is by tracking error over time using consistent metrics.